CBE shows better engine adaptivity than COLO, especially for extremely low or high achievement students¶

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · newest study 2020 · checked against its sources 2026-10-09 (automated, 1 of 1 entry) · not reviewed by a person · overdue for a recheck since 2023: tool and model accuracy changes quickly

Subclaims¶

q2 i? CBE's item difficulty matched student ability better than COLO's, with the advantage concentrated among extremely low or high achieving students. → Bo 2020

Evidence¶

Bo 2020¶

Bo, E., & Meyer, P. (2020). Comparability of MAP Growth tests administered through different technology and psychometric infrastructure: An engine evaluation study based on empirical data. Portland, OR: NWEA. https://www.nwea.org/research/publication/comparability-of-map-growth-tests-administered-through-different-technology-and-psychometric-infrastructure-an-engine-evaluation-study-based-on-empirical-data/

q2 · i? · causal · r2

Adaptivity evaluation based on delta values (difference between item difficulty and momentary theta), summarized in the report's executive summary; the article notes the simulation study by Hu et al. (2020) confirmed the precision and adaptivity findings. No effect size is printed.

"CBE shows better engine adaptivity than COLO, especially for extremely low or high achievement students. The capability of CBE in providing higher score precision and better adaptivity is also confirmed by the Project Altair simulation study (Hu et al., 2020)."

Discussion¶

Related Claims¶

• Adaptivity and score reliability of both engines depend on item-pool depth; the CBE often performed better than COLO for extreme low or high achievers when item banks were shallow — related
• The CBE and COLO engines met content specifications and recovered true scores well for the nine simulated MAP Growth tests — related
• Within a single administration, COLO administered more items and overexposed fewer items than the CBE, likely due to its randomesque exposure-control procedure — related
• Marginal reliabilities of MAP Growth winter scores are comparable across engines and all in the 0.90s, with CBE showing slightly higher precision (lower SEM) — related
• Item exposure rates are comparable across engines, with most items below 10%, and the CBE Reading item-use rate is lower than COLO's — related